scholarly journals Improved Formulation for the Optimization of Wind Turbine Placement in a Wind Farm

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
Zong Woo Geem ◽  
Junhee Hong
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Fossil Fuels ◽  
Optimal Placement ◽  
Branch And Bound Method ◽  
Optimal Layout ◽  
Objective Functions ◽  
Placement Problem ◽  
Optimization Formulation ◽  
The Cost

As an alternative to fossil fuels, wind can be considered because it is a renewable and greenhouse gas-free natural resource. When wind power is generated by wind turbines in a wind farm, the optimal placement of turbines is critical because different layouts produce different efficiencies. The objective of the wind turbine placement problem is to maximize the generated power while minimizing the cost in installing the turbines. This study proposes an efficient optimization formulation for the optimal layout of wind turbine placements under the resources (e.g., number of turbines) or budget limit by introducing corresponding constraints. The proposed formulation gave users more conveniences in considering resources and budget bounds. After performing the optimization, results were compared using two different methods (branch and bound method and genetic algorithm) and two different objective functions.

scholarly journals Wind Turbine Placement Optimization by means of the Monte Carlo Simulation Method

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
S. Brusca ◽  
R. Lanzafame ◽  
M. Messina
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Production ◽  
Wind Farm ◽  
Simulation Method ◽  
Optimal Placement ◽  
Monte Carlo Simulation Method ◽  
Energy Evaluation

This paper defines a new procedure for optimising wind farm turbine placement by means of Monte Carlo simulation method. To verify the algorithm’s accuracy, an experimental wind farm was tested in a wind tunnel. On the basis of experimental measurements, the error on wind farm power output was less than 4%. The optimization maximises the energy production criterion; wind turbines’ ground positions were used as independent variables. Moreover, the mathematical model takes into account annual wind intensities and directions and wind turbine interaction. The optimization of a wind farm on a real site was carried out using measured wind data, dominant wind direction, and intensity data as inputs to run the Monte Carlo simulations. There were 30 turbines in the wind park, each rated at 20 kW. This choice was based on wind farm economics. The site was proportionally divided into 100 square cells, taking into account a minimum windward and crosswind distance between the turbines. The results highlight that the dominant wind intensity factor tends to overestimate the annual energy production by about 8%. Thus, the proposed method leads to a more precise annual energy evaluation and to a more optimal placement of the wind turbines.

scholarly journals Evaluation of the impact of wind farm control techniques on fatigue and ultimate loads

2020 ◽  
Author(s):  
Alessandro Croce ◽  
Stefano Cacciola ◽  
Luca Sartori ◽  
Paride De Fidelibus
Keyword(s):  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Dynamic Responses ◽  
Control Techniques ◽  
Cost Of Energy ◽  
The Individual ◽  
The Cost ◽  
The Impact ◽  
Do So

Abstract. Wind farm control is one of the solutions recently proposed to increase the overall energy production of a wind power plant. A generic wind farm control is typically synthesized so as to optimize the energy production of the entire wind farm by reducing the detrimental effects due to wake-turbine interactions. As a matter of fact, the performance of a farm control is typically measured by looking mainly at the increase of produced power, possibly weighted with the wind Weibull and rose at a specific place, and, sometimes, by looking also at the fatigue loads. However, an aspect which is rather overlooked is the evaluation of the impact that a farm control law has on the maximum loads and on the dynamic responses under extreme conditions of the individual wind turbine. In this work, two promising wind farm controls, based respectively on Wake Redirection (WR) and Dynamic Induction Control (DIC) strategy, are evaluated at a single wind turbine level. To do so, a two-pronged analysis is performed. Firstly, the control techniques are evaluated in terms of the related impact on some specific key performance indicators (e.g. fatigue and ultimate loads, actuator duty cycle and annual energy production). Secondarily, an optimal blade redesign process, which takes into account the presence of the wind farm control, is performed with the goal of quantifying the possible modification in the structure of the blade and hence of quantifying the impact of the control on the Cost of Energy model.

scholarly journals Evaluation of the impact of active wake control techniques on ultimate loads for a 10 MW wind turbine

2022 ◽  
Vol 7 (1) ◽  
pp. 1-17
Author(s):  
Alessandro Croce ◽  
Stefano Cacciola ◽  
Luca Sartori
Keyword(s):  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Control Techniques ◽  
Control Optimization ◽  
Cost Of Energy ◽  
The Individual ◽  
The Cost ◽  
Wind Statistics ◽  
The Impact

Abstract. Wind farm control is one of the solutions recently proposed to increase the overall energy production of a wind power plant. A generic wind farm control is typically synthesized so as to optimize the energy production of the entire wind farm by reducing the detrimental effects due to wake–turbine interactions. As a matter of fact, the performance of a farm control is typically measured by looking at the increase in the power production, properly weighted through the wind statistics. Sometimes, fatigue loads are also considered in the control optimization problem. However, an aspect which is rather overlooked in the literature on this subject is the evaluation of the impact that a farm control law has on the individual wind turbine in terms of maximum loads and dynamic response under extreme conditions. In this work, two promising wind farm controls, based on wake redirection (WR) and dynamic induction control (DIC) strategy, are evaluated at the level of a single front-row wind turbine. To do so, a two-pronged analysis is performed. Firstly, the control techniques are evaluated in terms of the related impact on some specific key performance indicators, with special emphasis on ultimate loads and maximum blade deflection. Secondarily, an optimal blade redesign process is performed with the goal of quantifying the modification in the structure of the blade entailed by a possible increase in ultimate values due to the presence of wind farm control. Such an analysis provides for an important piece of information for assessing the impact of the farm control on the cost-of-energy model.

scholarly journals A general-purpose method for Pareto optimal placement of flow rate and concentration sensors in networked systems - With application to wastewater treatment plants

2020 ◽  
Author(s):  
Kris Villez ◽  
Peter A Vanrolleghem ◽  
lluis corominas
Keyword(s):  
Data Quality ◽  
High Speed ◽  
Wastewater Treatment Plants ◽  
Low Cost ◽  
Sensor Placement ◽  
General Purpose ◽  
Optimal Placement ◽  
Pareto Optimal ◽  
Placement Problem ◽  
The Cost

The advent of affordable computing, low-cost sensor hardware, and high-speed and reliable communications have spurred ubiquitous installation of sensors in complex engineered systems. However, ensuring reliable data quality remains a challenge. Exploitation of redundancy among sensor signals can help improving the precision of measured variables, detecting the presence of gross errors, and identifying faulty sensors. The cost of sensor ownership, maintenance efforts in particular, can still be cost-prohibitive however. Maximizing the ability to assess and control data quality while minimizing the cost of ownership thus requires a careful sensor placement. To solve this challenge, we develop a generally applicable method to solve the multi-objective sensor placement problem in systems governed by linear and bilinear balance equations. Importantly, the method computes all Pareto-optimal sensor layouts with conventional computational resources and requires no information about the expected sensor quality.

4. Wind power

2020 ◽  
pp. 47-59
Author(s):  
Nick Jelley
Keyword(s):  
Wind Power ◽  
Wind Turbines ◽  
Carbon Dioxide Emissions ◽  
Energy Demand ◽  
Wind Farm ◽  
Fossil Fuels ◽  
Wind Farms ◽  
Cost Competitiveness ◽  
Sea Wind ◽  
The Cost

‘Wind power’ focuses on wind-based power and its potential as a renewable energy source. Single wind turbines, both large and small, can be used to provide power to homes or a community. Wind turbines for large power generation are usually deployed in wind farms, which are arrays of turbines. These are located in regions where the wind conditions are good, such as exposed ridges, high-altitude plains, mountain passes, coastal areas, and out at sea. Wind power produces essentially no global warming nor any pollution; only a small amount of associated carbon dioxide emissions from the fossil fuels used in the construction and operation of the wind farms. And it takes less than a year for a wind farm to generate the same amount of energy used in its manufacture. The sharp fall in the cost of electricity from wind farms, corresponding to a 20 per cent learning rate over the last decade, is such that onshore wind farms have now achieved cost competitiveness (grid-parity) with fossil-fuel-fired generators. By 2050, it is estimated that about a seventh of the world’s energy demand could be met by wind power.

scholarly journals Multi-objective wind farm layout optimization using evolutionary computations

2019 ◽  
Vol 8 (4) ◽  
pp. 293
Author(s):  
Chandra Shekar ◽  
M. R Shivakumar
Keyword(s):  
Genetic Algorithm ◽  
Wind Turbine ◽  
Wind Power ◽  
Wind Farm ◽  
Fossil Fuels ◽  
Minimum Spanning Tree ◽  
Evolutionary Computations ◽  
Multi Objective ◽  
Wind Farm Design ◽  
Living Nature

<p class="Abstract">The usage of fossil fuels is actually not good for living nature and in future, this limited source of energy will vanish. Therefore, we need to go with the clean and renewable source of energy such as wind power, solar energy etc. In this paper, we are concentrating in wind power through optimizing the wind turbine placement in wind farm. The area-of-convex hull, maximize ‘output power’ and minimum spanning tree distance are our main objective topics, due to their effect in wind farm design. An implementation of modified version of the wind turbine (WT) placement model is uses to estimate the yields of the (wind farm) WF layouts and for simplifying the behavior of wind field, in this paper we uses a simple wake approach. Moreover, to resolve the multi-objective problem here we proposed (Modified Genetic Algorithm) MGA, which is considerably better than the (Genetic Algorithm) GA and for evaluate the performance of MGA we use the multi-objective (EA) evolutionary algorithms such as; Genetic algorithm (GA) and SPEA2 and, produce different number of WT layouts. These methodologies are consider with various ‘problematic specific operators’ that are present in this paper.</p>

scholarly journals A Comparative Study of Services Placement Algorithms in Future Networks: دراسة مقارنة لخوارزميّات توضيع الخدمات في الشّبكات المستقبليّة

2021 ◽  
Vol 5 (5) ◽  
pp. 64-51
Author(s):  
Manar Yacoub Al-Jabr, Ali Diab, Jomana diab Manar Yacoub Al-Jabr, Ali Diab, Jomana diab
Keyword(s):  
Optimal Placement ◽  
Management Service ◽  
Placement Problem ◽  
Qualitative Comparison ◽  
Comprehensive Knowledge ◽  
Future Networks ◽  
Placement Algorithms ◽  
Placement Algorithm ◽  
The Cost ◽  
The Ideal

The study aimed to analyze and compare several algorithms in the context of networks services placement, and then proposed a self-organized dynamic heuristic algorithm adaptable to continually changing network conditions in order to achieve the ideal placement of services replicas in future networks. It is known that future networks demand a high degree of self-organization to keep pace with ongoing changes while maintaining performance optimized. One of the important challenges in this context is the services placement problem. Service placement issue refers to the selection of the most appropriate network node for hosting a service. The ideal placement of services replicas reduces the cost of serving customers, improves connectivity between clients and servers as well as the use of available resources. The study summarized the results of qualitative comparison between several placement algorithms and refers to the most important requirements to be taken into account when implementing the placement algorithm. Generally, each service has its own placement technique, and the action taken by a specific service may affect other services decisions and force them to adapt. There is an urgent need to  a management service for managing services replicas to make the optimal placement decision. This service should work in a distributed manner and does not require comprehensive knowledge about the  network. It is also characterized by its ability to adapt to changing network conditions in terms of load and topology. Other services coordinate with the management service about replicating or migrating actions,  thus services will be offered  at a minimized cost.

Energy After COVID

2020 ◽  
Vol 119 (820) ◽  
pp. 317-322
Author(s):  
Michael T. Klare
Keyword(s):  
Renewable Energy ◽  
Electric Vehicles ◽  
Fossil Fuels ◽  
Fossil Fuel ◽  
White Collar ◽  
Peak Oil ◽  
Business Travel ◽  
Reduce Energy Consumption ◽  
The Cost ◽  
Energy Companies

By transforming patterns of travel and work around the world, the COVID-19 pandemic is accelerating the transition to renewable energy and the decline of fossil fuels. Lockdowns brought car commuting and plane travel to a near halt, and the mass experiment in which white-collar employees have been working from home may permanently reduce energy consumption for business travel. Renewable energy and electric vehicles were already gaining market share before the pandemic. Under pressure from investors, major energy companies have started writing off fossil fuel reserves as stranded assets that are no longer worth the cost of extracting. These shifts may indicate that “peak oil demand” has arrived earlier than expected.

Editor in Chief’s Note on the Green Hydrogen Fuel from Solar / Wind Power

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Seyed Ehsan Hosseini
Keyword(s):  
Solar Wind ◽  
Crude Oil ◽  
Fossil Fuels ◽  
Sustainable Energy ◽  
Green Energy ◽  
Hydrogen Fuel ◽  
Fuel Production ◽  
Crude Oil Prices ◽  
Trade War ◽  
The Cost

Renewable and sustainable energy has an evolving story as the ongoing trade war in the word is influencing crude oil prices. Moreover, the global warming is an inevitable consequence of the worldwide increasing rate of fossil fuel utilization which has persuaded the governments to invest on the clean and sustainable energy resources. In recent years, the cost of green energy has tumbled, making the price of renewables competitive to the fossil fuels. Although, the hydrogen fuel is still extremely expensive compared to the crude oil price, investigations about clean hydrogen fuel production and utilization has been developed significantly which demonstrate the importance of the hydrogen fuel in the future. This article aims to scrutinize the importance of green hydrogen fuel production from solar/wind energy.

Optimal Placement of FACTS Devices for Voltage Stability Improvement with Economic Consideration Using Firefly Algorithm

2019 ◽  
Vol 14 (1) ◽  
pp. 5-11
Author(s):  
S. Rajasekaran ◽  
S. Muralidharan
Keyword(s):  
Power Systems ◽  
Voltage Stability ◽  
Firefly Algorithm ◽  
Transmission System ◽  
Operating Conditions ◽  
Optimal Placement ◽  
Voltage Collapse ◽  
Facts Devices ◽  
The Cost ◽  
Bus System

Background: Increasing power demand forces the power systems to operate at their maximum operating conditions. This leads the power system into voltage instability and causes voltage collapse. To avoid this problem, FACTS devices have been used in power systems to increase system stability with much reduced economical ratings. To achieve this, the FACTS devices must be placed in exact location. This paper presents Firefly Algorithm (FA) based optimization method to locate these devices of exact rating and least cost in the transmission system. Methods: Thyristor Controlled Series Capacitor (TCSC) and Static Var Compensator (SVC) are the FACTS devices used in the proposed methodology to enhance the voltage stability of power systems. Considering two objectives of enhancing the voltage stability of the transmission system and minimizing the cost of the FACTS devices, the optimal ratings and cost were identified for the devices under consideration using Firefly algorithm as an optimization tool. Also, a model study had been done with four different cases such as normal case, line outage case, generator outage case and overloading case (140%) for IEEE 14,30,57 and 118 bus systems. Results: The optimal locations to install SVC and TCSC in IEEE 14, 30, 57 and 118 bus systems were evaluated with minimal L-indices and cost using the proposed Firefly algorithm. From the results, it could be inferred that the cost of installing TCSC in IEEE bus system is slightly higher than SVC.For showing the superiority of Firefly algorithm, the results were compared with the already published research finding where this problem was solved using Genetic algorithm and Particle Swarm Optimization. It was revealed that the proposed firefly algorithm gives better optimum solution in minimizing the L-index values for IEEE 30 Bus system. Conclusion: The optimal placement, rating and cost of installation of TCSC and SVC in standard IEEE bus systems which enhanced the voltage stability were evaluated in this work. The need of the FACTS devices was also tested during the abnormal cases such as line outage case, generator outage case and overloading case (140%) with the proposed Firefly algorithm. Outputs reveal that the recognized placement of SVC and TCSC reduces the probability of voltage collapse and cost of the devices in the transmission lines. The capability of Firefly algorithm was also ensured by comparing its results with the results of other algorithms.

Sign in / Sign up

Export Citation Format

Share Document